جست‌وجوی استاد و پژوهشگر

Corey T. Callaghanمشاهده پروفایل

استادیار

• Urban Ecology
• Citizen Science
• Biodiversity Data Science
• +۳ مورد دیگر

Dr. Corey T. Callaghan is an Assistant Professor in the Department of Wildlife Ecology and Conservation at the University of Florida . Based at the Fort Lauderdale Research and Education Center , his research focuses on global change ecology using big data from citizen science platforms like eBird and iNaturalist, combined with geospatial analyses and macroecological theory . Ph.D. (2019) from UNSW Sydney M.S. (2015) from Florida Atlantic University B.S. + B.S. (2013) from Canisius College His work examines urban ecology , including how species traits influence urban tolerance across birds, amphibians, and butterflies. He develops adaptive sampling frameworks to optimize citizen science data collection while addressing biases. Current projects analyze human-nature interactions through citizen science participation, secondary data in photographs, and machine learning for biodiversity monitoring. He actively contributes to conservation strategies for urban biodiversity and data-driven restoration efforts . Recent publications highlight his expertise in cross-taxa comparisons , continental-scale analyses , and ecosystem service quantification . He leads the Global Ecology Research Group at the University of Florida, emphasizing collaborative science and open-source methodologies .

• Machine Learning
• Computer Vision
• Data Mining
• +۶ مورد دیگر

Dr. Chang Xu is an Associate Professor in Machine Learning and Computer Vision at the University of Sydney's School of Computer Science. He holds a Bachelor of Engineering from Tianjin University and a PhD from Peking University. His research focuses on machine learning, data mining, and their applications in AI and computer vision, including multi-view learning, visual search, and face recognition. He is an ARC Future Fellow and a member of the Sydney Southeast Asia Centre and The Net Zero Institute. Education: B.E. in Engineering (Tianjin University), Ph.D. in Computer Science (Peking University). His research interests emphasize handling heterogeneous data, exploring data variety, and developing algorithms for robust AI systems. His work includes adversarial robustness, neural architecture search, and efficient deep learning models. Research trends in his articles include adversarial robustness in neural architectures, efficient vision transformers, multimodal 3D style transfer, and underwater image restoration. Key contributions span image restoration, video super-resolution, and lightweight network design. He has advised multiple PhD and master's students on topics like diffusion models, radar image synthesis, and graph similarity. Awards: ARC Future Fellow. Collaborations focus on cross-domain data integration and AI applications. His labs and teams explore generative models, robust learning, and scalable robotics policies. Recent work includes diffusion models for action segmentation and robust vision-language systems.

• Deep Reinforcement Learning
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

David Silver is a Professor of Computer Science at University College London and Principal Research Scientist at DeepMind, leading the Reinforcement Learning Research Group. His pioneering work in deep reinforcement learning has revolutionized artificial intelligence through breakthroughs in computer game-playing algorithms. His educational background includes: Bachelor's and Master's degrees from Cambridge University (1997, 2000) PhD in Computer Science from the University of Alberta (2009) Silver specializes in deep reinforcement learning where algorithms learn through trial-and-error in interactive environments. His research combines deep neural networks with reinforcement learning strategies to solve complex decision-making problems. He is renowned for developing AlphaGo (defeating Go world champion Lee Sedol in 2016), AlphaZero (mastering Chess, Shogi and Go through self-play), and AlphaStar (conquering Starcraft II). His work demonstrates unprecedented generality in game-playing AI and has catalyzed industry-wide adoption of reinforcement learning techniques. Analysis of his publications reveals a consistent trajectory toward self-supervised learning systems. His 2015-2016 Nature papers established foundational architectures combining neural networks with Monte Carlo tree search, shifting the field from human-data dependency toward pure self-play methodologies. This evolution enabled superhuman performance across diverse game domains while minimizing domain-specific knowledge. His scientific awards include: ACM Prize in Computing (2019) for breakthrough advances in computer game-playing Marvin Minsky Medal (2018) for outstanding achievements in AI Royal Academy of Engineering Silver Medal (2017) for UK engineering contributions Mensa Foundation Prize (2017) for best AI scientific discovery Silver's research has generated significant real-world impact beyond gaming, including optimizing the UK power grid, reducing Google data center energy consumption, and planning European Space Agency probe trajectories. While not explicitly documented in advising roles, his leadership at DeepMind fosters collaborative research environments that train next-generation AI scientists through high-impact projects. As lead of DeepMind's Reinforcement Learning Research Group, Silver directs cutting-edge work extending deep reinforcement learning to robotics, complex real-world systems, and multi-agent environments. Current initiatives focus on transferring game-playing breakthroughs to industrial automation and scientific discovery applications.

Russell Epsteinمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Behavioral Neuroscience
• Spatial Navigation
• +۴ مورد دیگر

Russell Epstein is a Professor and Director of Graduate Studies in the Department of Psychology at the University of Pennsylvania. He is affiliated with the Center for Cognitive Neuroscience and Goddard Labs. His research focuses on neural mechanisms underlying visual scene perception, spatial navigation, and memory. Epstein holds a BA in Physics from the University of Chicago and a PhD in Applied Mathematics from Harvard University. Epstein’s research interests include high-level vision, spatial cognition, and the neural basis of environmental representations. His lab uses functional MRI and cognitive neuroscience techniques to study how scenes, objects, landmarks, and spaces are encoded in brain systems such as the parahippocampal place area and retrosplenial cortex. Recent work explores cognitive maps, grid-like neural representations, and the role of multisensory cues in navigation. His articles emphasize spatial navigation strategies, hierarchical cognitive maps, and the interplay between perception and memory. Notable contributions include investigations into hippocampal spatial metrics, olfactory navigation, and the neural underpinnings of environmental learning. Epstein teaches courses on cognitive neuroscience, including PSYC 149 and PSYC 600. He advises two graduate students in Psychology and has no listed scientific awards. His work is supported by grants (unspecified) and conducted within collaborative teams at the Center for Cognitive Neuroscience. Epstein’s research extends to labs focused on spatial cognition and neuroimaging, advancing understanding of how humans mentally map environments through visual and sensory integration.

Minh Q. Phanمشاهده پروفایل

دانشیار

• System Identification
• Control Theory
• Robotics
• +۴ مورد دیگر

Minh Q. Phan is an Associate Professor of Engineering at Dartmouth College's Thayer School of Engineering. His expertise spans system identification, iterative learning control, model predictive control, robotic swarm control, and intelligent control systems. He holds a BS from the University of California, Berkeley, and MS/M.Phil/PhD degrees from Columbia University in Mechanical Engineering. Dr. Phan has contributed to over 50 peer-reviewed publications and serves as an Associate Editor for the Journal of Guidance, Control, and Dynamics. His research focuses on advancing control theory applications in robotics, structural health monitoring, and sustainable construction materials. Key contributions include the development of OKID (Observer/Kalman Filter Identification) methods and bilinear system identification frameworks. Education History: Bachelor of Science in Mechanical Engineering, UC Berkeley, 1985 Master of Science in Mechanical Engineering, Columbia University, 1986 Master of Philosophy in Mechanical Engineering, Columbia University, 1988 Doctor of Philosophy in Mechanical Engineering, Columbia University, 1989 Research Interests: Advanced control methodologies for dynamic systems Model-based predictive control strategies Applications in robotics and aerospace engineering Structural health monitoring via system identification Machine learning for materials science Teaching Responsibilities include courses like ENGG 149 (Systems Identification), ENGS 145 (Modern Control Theory), and ENGG 148 (Structural Mechanics). His work bridges theoretical control systems with practical industrial applications, including automation in food processing and sustainable construction practices. Dr. Phan has collaborated on projects addressing viral epidemiology in Vietnam and coastal erosion mitigation strategies.

• Computer Vision
• Robotics
• 3D Data Understanding
• +۳ مورد دیگر

Hao Su is an Associate Professor in the Department of Computer Science and Engineering at University of California, San Diego . He serves as Chairman & CTO of Hillbot Inc , and leads the SU Lab which focuses on building autonomous systems that learn actively in physical environments. His affiliations include the Institute for Learning-enabled Optimization at Scale , Artificial Intelligence Group , Contextual Robotics Institute , Halicioğlu Data Science Institute , and Center for Visual Computing . As a researcher in Computer Vision, Robotics, and Neural Geometry , he has made significant contributions to 3D foundation models, reward-free world models, diffusion policy frameworks, and GPU-accelerated simulation environments. His 2024-2025 publications include advancements in hand-eye calibration, dynamic mesh reconstruction, and multi-stage robotic manipulation. His scientific awards include: Frontiers of Science Award (2025) TPAMI Young Research Award (2025) NSF CAREER Award (2023) ACM SIGGRAPH Best Doctorate Thesis Honorable Mention (2019) He has served as Program Chair for CVPR 2025 and Area Chair for ICLR 2022 and NeurIPS 2023 , while previously serving as Publication Chair for 3DV 2016 and Program Committee for SIGGRAPH Asia Workshops .

• Machine Learning
• Natural Language Processing
• Music Information Retrieval
• +۱۲ مورد دیگر

Colin Raffel , currently an Associate Professor at the University of Toronto and Associate Research Director at the Vector Institute , is a leading researcher in machine learning and natural language processing . His career spans roles at Hugging Face (Faculty Researcher), Google Brain (Senior Research Scientist), and UNC Chapel Hill (Assistant Professor). Education: PhD in Electrical Engineering (Columbia), MA in Music/Science (Stanford), BA in Mathematics (Oberlin) Key affiliations: Google Brain (2016-2020), Hugging Face (2021-present), Vector Institute (2023-present) His research focuses on language model development , attention mechanisms , efficient machine learning , and music information retrieval . Recent work explores model merging , parameter-efficient fine-tuning , and data-constrained language models . Teaching : Has instructed courses at University of Toronto and UNC Chapel Hill on Neural Networks , Deep Learning , and Information Theory . Academic service includes organizing ICLR workshops and serving as Senior Area Chair for NeurIPS and EMNLP . Notable awards : NSF CAREER (2022), Caspar Bowden Award (2023), NeurIPS Outstanding Paper (2023) Key contributions : Core developer of WT5 , Git-Theta , and mir_eval software

• Machine Learning
• Natural Language Processing
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Luke Zettlemoyer is an Adjunct Professor of Computer Science and Engineering at the University of Washington, with affiliations to the Department of Linguistics. He focuses on machine learning, natural language processing, and multimodal systems, contributing to advancements in large language models, ethical AI, and scalable architectures. His research addresses challenges in model alignment, generalization, and cross-domain integration. Key research interests include multimodal reward models, efficient tokenization strategies, and model optimization techniques. He has explored topics such as neural trajectories for robot learning, content-adaptive image processing, and ethical mitigation of verbatim data reproduction. His publications span 2023–2025, emphasizing practical applications of AI in robotics, vision-language systems, and scalable retrieval-based models. While no formal awards are listed, his work reflects significant contributions to foundational AI research.

• Complex Systems
• Financial Mathematics
• Statistical Physics
• +۶ مورد دیگر

Tomaso Aste is a Professor of Complexity Science at the Department of Computer Science, University College London (UCL). He founded the Financial Computing and Analytics group and co-founded the UCL Centre for Blockchain Technologies. His work bridges complex systems, data science, and finance, with applications in blockchain, fintech, and market modeling. Education: PhD in Physics (Politecnico di Milano, 1994); Laurea in Physics (University of Genoa, 1990) Prior Appointments: Reader at University of Kent's School of Physics; Associate Professor at Australian National University's Applied Mathematics His research focuses on data-driven modeling of complex systems , particularly financial systems, complex networks, and statistical physics. He has pioneered information filtering networks and topological machine learning methods for financial applications, including portfolio optimization, risk assessment, and cryptocurrency analysis. Recent publications highlight his expertise in financial time-series analysis, blockchain technology, and AI-driven modeling. Articles explore topics like limit order books, cryptocurrency market fragility, and topological neural networks. His work has influenced regulatory technology (RegTech) frameworks and digital economy strategies. Scientific Awards : Marie Curie Individual Fellowship University of Genoa graduate study specialization Fellowship Bacheflor Boncompagni-Ludovisi Foundation Fellowship Awarded fellowships from European Commission and academic foundations support his interdisciplinary research. He has held editorial roles at journals like Philosophical Magazine and Granular Matter , and contributed to professional societies including American Physical Society and Australian Research Council panels. Teaching & Academic Leadership : Co-created four UCL Master's programs: Financial Risk Management, Computational Finance, Financial Technologies, Emerging Digital Technologies Coordinates executive training on AI, blockchain, fintech, and regtech for regulators and private firms Teaches graduate-level courses in Data-Driven Modeling, Data Science, and Advanced AI

Walter Leal Filhoمشاهده پروفایل

استاد

• Climate Change
• Sustainability
• Environmental Management
• +۳ مورد دیگر

Prof. Walter Leal Filho is a distinguished academic and researcher holding professorial positions at Hamburg University of Applied Sciences (Germany) and Manchester Metropolitan University (UK). He is the founding director of the European School of Sustainability Science and Research (ESSSR) and the Inter-University Sustainable Development Research Programme (IUSDRP). With over 30 years of editorial experience, he has authored over 500 publications, focusing on sustainability, climate change, and environmental management. His research interests span Climate Change, Urban Resilience, Natural Resource Management, and Sustainability Education. He emphasizes interdisciplinary approaches to address global challenges, such as space debris mitigation and bio-based materials for sustainable packaging. His work bridges policy, education, and practical solutions for sustainable development. Prof. Leal Filho’s recent articles highlight trends in sustainable urban planning, space sustainability, and ecosystem conservation in the Amazon. He has been recognized as a Top Cited Scholar 2024, reflecting his impactful contributions. With 1,200+ co-authors and a global network, he collaborates widely, fostering international research and education initiatives. As director of ESSSR and IUSDRP, he leads programs advancing sustainability science and interdisciplinary research. His academic leadership and prolific publications underscore his role as a pivotal figure in global sustainability efforts.

Alan Ritterمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Alan Ritter is an Associate Professor at the School of Interactive Computing , Georgia Institute of Technology, with additional affiliation to the Machine Learning Center . His research focuses on Natural Language Processing , particularly robust models across domains/languages with fewer labels and efficient resource use, plus data-driven dialogue agents for open-topic conversations. Research Interests : Robust NLP models, cross-lingual transfer, resource-efficient learning, dialogue systems, cultural bias measurement, and privacy-aware language models Students : Mentors Ph.D. students in Georgia Tech's ML and CS programs, including Junmo Kang, Yang Chen, and Duong Minh Le. Alumni include Fan Bai (Ph.D. 2023), Yang Chen (Ph.D. 2024), and Andrew Li (M.S. 2024). Awards : NSF CAREER Award, Amazon Research Award, ACL 2024 Best Social Impact Paper, IUI 2009 Best Student Paper. Recent Work : Studies training budget allocation between supervised and preference-based finetuning, cross-lingual information extraction, cultural bias in LLMs, and privacy risk mitigation in social media disclosures. Service : Served as Program Chair for NAACL 2025, Area Chair for multiple top-tier conferences (COLM, EMNLP, ACL, EACL, AAAI). Email : alan.ritter@cc.gatech.edu

Mary Bucholtzمشاهده پروفایل

استاد

• Sociocultural Linguistics
• Language and Identity
• Language and Race
• +۱۰ مورد دیگر

Mary Bucholtz is a Professor in the Department of Linguistics at the University of California, Santa Barbara (UCSB). She holds affiliations with multiple departments including Anthropology, Feminist Studies, Spanish and Portuguese, the Gevirtz Graduate School of Education, Comparative Literature, and Latin American and Iberian Studies. Her research integrates sociocultural linguistics with anthropological, gender, and social justice frameworks. Education: PhD in Linguistics, University of California, Berkeley (1997) Bucholtz's work examines how language shapes and is shaped by social identities, particularly among youth, through dimensions like race, gender, and cultural practices. She emphasizes community-centered research , linguistic activism , and interdisciplinary methodologies to address systemic inequalities. Recent publications explore affective agency in Latinx youth, educational equity, and antiracist linguistics. Her collaborative projects often involve partnerships with educational institutions and youth communities in California, focusing on translanguaging , Black language justice , and raciolinguistic ideologies . Grants from the National Science Foundation, Spencer Foundation, and Wenner-Gren Foundation support her research. She co-edited the open-access volumes Decolonizing Linguistics and Inclusion in Linguistics (Oxford University Press, 2024), alongside authoring White Kids: Language, Race, and Styles of Youth Identity (Cambridge, 2011) and Talking College: Making Space for Black Language Practices in Higher Education (Teachers College Press, 2022).

Peninah Murageمشاهده پروفایل

استادیار

• Environmental Epidemiology
• Climate Change
• Health Geography
• +۵ مورد دیگر

Dr Peninah Murage is an Assistant Professor at the London School of Hygiene & Tropical Medicine in the Department of Public Health, Environments and Society under the Faculty of Public Health and Policy. She specializes in environmental epidemiology with a PhD in Health Geography and focuses on health impacts of environmental changes, particularly climate change mitigation and adaptation strategies. Affiliation: Centre on Climate Change and Planetary Health Her research explores climate change effects on health outcomes like heat-related mortality, cardiovascular diseases, and cognitive development in children. She integrates GIS/spatial analysis with public health and policy frameworks to identify nature-based solutions for sustainable development. Current work examines systemic inequalities in heat risk exposure and interventions such as tree-based strategies in low-income settings. Key grants include: Health Protection Research Unit on Climate Change and Health Security (2025-2030, NIHR) Climate Change and Non-Communicable Diseases in Senegal (2024-2027) Pathfinder 2: Accelerating Climate Action for Health (2023-2026) She actively contributes to the Lancet Pathfinder Commission and serves on the Executive Committee of the International Society of Environmental Epidemiology (African Chapter).

Katherine Brickellمشاهده پروفایل

استاد

• Social Geography
• Cultural Geography
• Historical Geography
• +۱۰ مورد دیگر

Katherine Brickell is Professor of Human Geography at Royal Holloway, University of London (RHUL), where she serves as Research Lead for the Department of Geography. She is editor of the journal Gender, Place and Culture and former Chair of the RGS-IBG Gender and Feminist Geographies Research Group. Her work spans social, political, development, urban and legal geography with a feminist orientation. Brickell's research centers on three interconnected themes: home and home unmaking, labor precarity, and feminist legal geographies. Her longstanding interest in the domestic sphere and home unmaking aims to reaffirm the home as a political entity. Her monograph Home SOS: Gender, Violence and Survival in Crisis Ordinary Cambodia brings together 15 years of research on domestic violence and forced eviction. Since 2017, she has conducted collaborative work in London and Dublin on modular housing for homeless families. She has also led significant research on labor conditions in Cambodia, including the ESRC-DFID funded 'Blood Bricks' project (2016-2019) studying climate change impacts on rural families migrating to brick kilns. Her recent publications reveal a strong focus on debt, microfinance, and climate vulnerability in Cambodia, with multiple 2022-2024 articles examining how over-indebtedness intersects with social reproduction and climate adaptation. Her work consistently applies feminist lenses to understand spatial dimensions of power, particularly in Southeast Asia. Brickell has published in top journals including Transactions of the Institute of British Geographers , Progress in Human Geography , Antipode , and Annals of the American Association of Geographers . Gill Memorial Award (2014) Philip Leverhulme Prize (2016) Times Higher Education Research Project of the Year (2020) Brickell has supervised numerous doctoral students and mentored postdoctoral fellows working on topics including remittances during COVID-19, climate mobilities, moral geographies of garment work, and women's experiences with domestic violence. Her research has been funded by ESRC-DFID, UKRI GCRF, and the Urban Studies Foundation, among others. She collaborates extensively with colleagues in Cambodia and across Europe, with current projects examining climate resilience, credit-taking, and nutrition in Cambodia and South India, as well as the economic impacts of the pandemic on Cambodian garment workers.

Jiaxuan Youمشاهده پروفایل

استادیار

• Graph Neural Networks
• Relational Data
• Machine Learning Systems
• +۹ مورد دیگر

Jiaxuan You is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois at Urbana-Champaign, leading the U Lab focused on achieving Artificial General Intelligence (AGI) in digital environments. His research spans graph neural networks (GNNs), relational data, foundation models, and machine learning systems. PhD and MS in Computer Science from Stanford University (2021) Developed GraphGym and PyTorch Geometric (PyG) for graph learning Core member at Kumo AI (2021-2023) His research explores: Graph-enhanced LLMs: Integrating relational structures into foundation models AGI Development: Self-optimizing AI agents and tool utilization ML Systems: Scalable architectures and redundancy-free computation Interdisciplinary Applications: Financial networks, crop yield prediction, and metro systems Recent publications focus on temporal reasoning, multi-agent dynamics, and hybrid architectures for LLMs. He actively develops open-source tools like DBGYM and GraphRouter. Scientific recognition includes: JPMC PhD Fellowship Baidu Scholarship Best Student Paper at AAAI 2017 World Bank Big Data Innovation Challenge winner He mentors PhD and intern students, emphasizing machine learning systems expertise. His lab collaborates on AGI workshops (e.g., ICLR 2024) and industry projects.